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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            High   Low  Open  Close      Volume  Adj Close\n",
      "Date                                                      \n",
      "2017-01-03  4.79  4.75  4.76   4.77   7883000.0   4.448430\n",
      "2017-01-04  4.85  4.79  4.80   4.84  10247100.0   4.513710\n",
      "2017-01-05  4.92  4.83  4.85   4.90   9878400.0   4.569665\n",
      "2017-01-06  4.99  4.90  4.93   4.92  18078800.0   4.588317\n",
      "2017-01-09  4.88  4.78  4.86   4.83  14554000.0   4.504384\n",
      "            High   Low  Open  Close      Volume  Adj Close\n",
      "Date                                                      \n",
      "2019-01-03  5.65  5.56  5.64   5.57  17354500.0       5.57\n",
      "2019-01-04  5.96  5.73  5.73   5.93  34666300.0       5.93\n",
      "2019-01-07  6.09  5.93  5.95   6.02  25502600.0       6.02\n",
      "2019-01-08  6.16  6.03  6.07   6.15  33497100.0       6.15\n",
      "2019-01-09  6.24  6.14  6.16   6.21  25471600.0       6.21\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from pandas  import Series, DataFrame\n",
    "\n",
    "import pandas_datareader as pdr\n",
    "import pandas_datareader.data as web\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# %matplotlib inline\n",
    "\n",
    "import datetime\n",
    "\n",
    "start = datetime.datetime(2017,1,1)\n",
    "end = datetime.date.today()\n",
    "# stock = web.DataReader(\"600519.SS\", \"yahoo\", start, end)\n",
    "stock = web.DataReader(\"NOK\", \"yahoo\", start, end)\n",
    "#print(stock)\n",
    "print(stock.head())\n",
    "print(stock.tail())\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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